Associate Director, AI for Discovery - New Target Discovery

AstraZeneca; Kendall Square (MA); On-site; USD 180,000 - 240,000; Full time

Job summary

AstraZeneca in Cambridge, MA, is seeking an Associate Director for AI in Discovery to lead AI-enabled target discovery. You will apply agentic AI and predictive biology models to identify and validate new drug targets across Oncology and BioPharmaceuticals, collaborating with cross-functional teams and external collaborators.

You will guide development of AI pipelines, publish findings, and help shape the scientific strategy for translating AI advances into therapies.

Qualifications

• PhD in computational biology, bioinformatics, AI/ML, systems biology with 5+ years post-doctoral/industry experience.
• Demonstrated expertise in agentic AI, LLM-based reasoning systems, or multi-agent architectures applied to scientific problems.
• Experience with predictive AI modeling for biology—foundation models, graph neural networks, perturbation models, or virtual cell approaches.
• Deep understanding of drug discovery biology: target identification, target validation, mechanism of action, translational science.
• Strong Python proficiency; production-quality code and pipelines for scientific applications.
• Hands-on experience with deep learning frameworks (PyTorch, JAX, or equivalent).
• Ability to influence cross-functional teams as a technical expert and strategic contributor.
• Strong scientific communication with publications or collaborations.

Responsibilities

• Identify high-impact use cases with cross-functional scientists for AI-driven target discovery.
• Deploy multi-agent AI systems into biology workflows and translate AI capabilities into insights.
• Advise on AI-driven target prioritization and investment decisions.
• Develop and benchmark predictive models for in silico biology (perturbation, virtual cells, etc.).
• Contribute to scientific strategy and roadmap with senior leadership.
• Increase external visibility through publications and conferences.
• Operate autonomously as a technical subject matter expert across teams.

Skills

Python

Deep learning

Agentic AI

Multi-agent systems

Scientific communication

Education

PhD in computational biology, bioinformatics, AI/ML, systems biology

Tools

PyTorch

JAX

Job description

Associate Director, AI for Discovery - New Target Discovery

Location: Cambridge, MA US (Kendall Square)

Salary: Competitive + Excellent Benefits

About AstraZeneca

At AstraZeneca, we put patients first and strive to meet their unmet needs worldwide. Working here means being entrepreneurial, thinking big and working together to make the impossible a reality. If you are swift to action, confident to lead, willing to collaborate, and curious about what science can do, then you're our kind of person.

We are a global, science-driven biopharmaceutical company dedicated to discovering, developing, and delivering innovative medicines that enrich the lives of patients. Our R&D engine combines deep biology expertise with cutting-edge artificial intelligence to accelerate how we find and validate new drug targets - ultimately bringing life-changing therapies to patients faster.

About Our Site

Our Cambridge, MA site at 290 Binney Street in Kendall Square is a 570,000-square-foot, state-of-the-art facility that consolidates approximately 1,500 R&D, commercial, and corporate employees. Positioned within the world's leading life sciences and biotech innovation cluster, the site is designed to foster deep collaboration with neighboring academic institutions, healthcare networks, and biotech partners. The facility features advanced laboratory infrastructure, a dedicated conferencing center, and a high-performance workplace designed to balance natural daylight, collaboration, and employee comfort.

About the Team

The AI for Discovery - New Target Discovery team exists to surface novel drug targets that Oncology and BioPharmaceuticals R&D can act on. We accelerate discovery by building and deploying two core AI capabilities: agentic AI and predictive models of biology to accelerate new target decision making across AZ R&D.

Our team supports both Oncology and BioPharmaceuticals therapeutic areas, sharing learnings across target discovery approaches and connecting new target strategy across AstraZeneca disease areas. We partner closely with therapeutic area scientists in Oncology, CVRM, Respiratory, Immunology, and Infectious Disease - as well as AI engineering and AI research teams.

What the Role Involves

This is an expert, hands-on role at the intersection of artificial intelligence and drug discovery biology. You will bring deep technical expertise in AI andb

Key Responsibilities

• Partner with therapeutic area scientists to identify high-impact use cases where agentic AI and predictive models can accelerate target identification and validation.
• Apply technical expertise to deploy multi-agent AI systems into therapeutic area workflows, translating cutting-edge AI capabilities into actionable scientific insights.
• Advise cross-functional matrix project teams on leveraging AI-driven approaches for target prioritization and investment decisions.
• Contribute to the development and benchmarking of predictive foundation models for in silico biology - including perturbation prediction, virtual cell models, and preclinical efficacy forecasting.
• Contribute to the team's scientific strategy and roadmap in close partnership with the Senior Director and team members.
• Build AstraZeneca's external visibility through publications, conference presentations, and scientific collaborations.
• Act autonomously as a subject matter expert, influence through technical credibility, and drive outcomes across organizational boundaries.

Essential Skills

• PhD in computational biology, bioinformatics, AI/ML, systems biology, or a related quantitative discipline, with 5+ years of post-doctoral and/or industry experience.
• Demonstrated expertise in agentic AI, LLM-based reasoning systems, or multi-agent architectures applied to scientific problems.
• Experience with predictive AI modeling for biology - foundation models, graph neural networks, perturbation models, or virtual cell approaches.
• Deep understanding of drug discovery biology: target identification, target validation, mechanism of action, or translational science.
• Strong technical proficiency in Python (required); experience building production-quality code, pipelines, and tools for scientific applications.
• Hands-on experience with deep learning frameworks (PyTorch, JAX, or equivalent) for model development and evaluation.
• Ability to influence cross-functional teams as a technical expert and strategic contributor.
• Strong scientific communication - track record of publications, conference presentations, or external collaborations.

Desirable Skills

• Experience with multi-agent orchestration frameworks or scientific reasoning platforms.
• Knowledge of targeted delivery modalities such as antibody-drug conjugates (ADCs), bispecifics, or degraders.
• Experience integrating multimodal biological data (genomics, transcriptomics, proteomics, functional